Tootfinder

AD-NEv : The multi-architecture neuroevolution-based multivariate anomaly detection framework
Marcin Pietro\'n, Dominik \.Zurek, Kamil Faber, Roberto Corizzo
https://arxiv.org/abs/2404.07968

AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework
Anomaly detection tools and methods enable key analytical capabilities in modern cyberphysical and sensor-based systems. Despite the fast-paced development in deep learning architectures for anomaly detection, model optimization for a given dataset is a cumbersome and time-consuming process. Neuroevolution could be an effective and efficient solution to this problem, as a fully automated search method for learning optimal neural networks, supporting both gradient and non-gradient fine tuning. H…

The Role of Confidence for Trust-based Resilient Consensus (Extended Version)
Luca Ballotta. Michal Yemini
https://arxiv.org/abs/2404.07838 https://…

The Role of Confidence for Trust-based Resilient Consensus (Extended Version)
We consider a multi-agent system where agents aim to achieve a consensus despite interactions with malicious agents that communicate misleading information. Physical channels supporting communication in cyberphysical systems offer attractive opportunities to detect malicious agents, nevertheless, trustworthiness indications coming from the channel are subject to uncertainty and need to be treated with this in mind. We propose a resilient consensus protocol that incorporates trust observations f…

Homology of Moment Frames
Zoe Cooperband, Allan McRobie, Cameron Millar, Bernd Schulze
https://arxiv.org/abs/2404.07184 https://arxiv…

Homology of Moment Frames
Using homological techniques we show that a pin-anchored frame that involves only moments and shears provides a conceptual bridge between the statics of moment frames and the kinematics of pin-jointed trusses. One immediate result is a long exact sequence whose alternating sum of dimensions gives a novel counting rule for self-stresses and mechanisms. This combines the Maxwell-Calladine count for pin-jointed trusses with the circuit rank (first Betti number) associated with self-stresses in mom…

Cyberbully and Online Harassment: Issues Associated with Digital Wellbeing
Manasi Kulkarni (Department of Industrial & Systems Engineering, University of Michigan-Dearborn, MI, USA), Siddhi Durve (Department of Industrial & Systems Engineering, University of Michigan-Dearborn, MI, USA), Bochen Jia (Department of Industrial & Systems Engineering, University of Michigan-Dearborn, MI, USA)
https://arxiv.org/abs/2404.18989 https://arxiv.org/pdf/2404.18989
arXiv:2404.18989v1 Announce Type: new
Abstract: As digital technology becomes increasingly embedded in daily life, its impact on social interactions has become a critical area of study, particularly concerning cyberbullying. This meta-analysis investigates the dual role of technology in cyberbullying both as a catalyst that can exacerbate the issue and as a potential solution. Cyberbullying, characterized by the use of digital platforms to harass, threaten, or humiliate individuals, poses significant challenges to mental and social wellbeing. This research synthesizes empirical findings from diverse studies to evaluate how innovative technological interventions, such as content monitoring algorithms, anonymous reporting systems, and educational initiatives integrated within digital platforms, contribute to reducing the prevalence of cyberbullying. The study focuses on the effectiveness of these interventions in various settings, highlighting the need for adaptive strategies that respond to the dynamic digital landscape. By offering a comprehensive overview of the current state of cyberbullying and the efficacy of technology based solutions, this analysis provides valuable insights for stakeholders, including educators, policymakers, and technology developers, aiming to enhance digital wellbeing and create safer online environments. The findings underscore the importance of leveraging technology not only as a medium of communication but also as a strategic tool to combat the negative impacts of cyberbullying, thus promoting a more inclusive and respectful digital world.

This https://arxiv.org/abs/2402.16458 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

D-XCB: Data-independent Debiasing for Fair and Accurate Transformer-based Cyberbullying Detection
Swear words are a common proxy to collect datasets with cyberbullying incidents. Our focus is on measuring and mitigating biases derived from spurious associations between swear words and incidents occurring as a result of such data collection strategies. After demonstrating and quantifying these biases, we introduce ID-XCB, the first data-independent debiasing technique that combines adversarial training, bias constraints and debias fine-tuning approach aimed at alleviating model attention to …

A Piece of Theatre: Investigating How Teachers Design LLM Chatbots to Assist Adolescent Cyberbullying Education
Michael A. Hedderich, Natalie N. Bazarova, Wenting Zou, Ryun Shim, Xinda Ma, Qian Yang
https://arxiv.org/abs/2402.17456

A Piece of Theatre: Investigating How Teachers Design LLM Chatbots to Assist Adolescent Cyberbullying Education
Cyberbullying harms teenagers' mental health, and teaching them upstanding intervention is crucial. Wizard-of-Oz studies show chatbots can scale up personalized and interactive cyberbullying education, but implementing such chatbots is a challenging and delicate task. We created a no-code chatbot design tool for K-12 teachers. Using large language models and prompt chaining, our tool allows teachers to prototype bespoke dialogue flows and chatbot utterances. In offering this tool, we explore te…

Safety Verification of Wait-Only Non-Blocking Broadcast Protocols
Lucie Guillou, Arnaud Sangnier, Nathalie Sznajder
https://arxiv.org/abs/2403.18591 https:…

Safety Verification of Wait-Only Non-Blocking Broadcast Protocols
We study networks of processes that all execute the same finite protocol and communicate synchronously in two different ways: a process can broadcast one message to all other processes or send it to at most one other process. In both cases, if no process can receive the message, it will still be sent. We establish a precise complexity class for two coverability problems with a parameterised number of processes: the state coverability problem and the configuration coverability problem. It is alr…

CoverUp: Coverage-Guided LLM-Based Test Generation
Juan Altmayer Pizzorno, Emery D. Berger
https://arxiv.org/abs/2403.16218 https://a…

CoverUp: Coverage-Guided LLM-Based Test Generation
This paper presents CoverUp, a novel system that drives the generation of high-coverage Python regression tests via a combination of coverage analysis and large-language models (LLMs). CoverUp iteratively improves coverage, interleaving coverage analysis with dialogs with the LLM to focus its attention on as yet uncovered lines and branches. The resulting test suites significantly improve coverage over the current state of the art: compared to CodaMosa, a hybrid LLM / search-based software test…

Safety Verification of Wait-Only Non-Blocking Broadcast Protocols
Lucie Guillou, Arnaud Sangnier, Nathalie Sznajder
https://arxiv.org/abs/2403.18591 https:…

Safety Verification of Wait-Only Non-Blocking Broadcast Protocols
We study networks of processes that all execute the same finite protocol and communicate synchronously in two different ways: a process can broadcast one message to all other processes or send it to at most one other process. In both cases, if no process can receive the message, it will still be sent. We establish a precise complexity class for two coverability problems with a parameterised number of processes: the state coverability problem and the configuration coverability problem. It is alr…

This https://arxiv.org/abs/2403.18314 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Chinese Offensive Language Detection:Current Status and Future Directions
Despite the considerable efforts being made to monitor and regulate user-generated content on social media platforms, the pervasiveness of offensive language, such as hate speech or cyberbullying, in the digital space remains a significant challenge. Given the importance of maintaining a civilized and respectful online environment, there is an urgent and growing need for automatic systems capable of detecting offensive speech in real time. However, developing effective systems for processing la…